spatstat.core (version 2.3-1)

simulate.slrm: Simulate a Fitted Spatial Logistic Regression Model

Description

Generates simulated realisations from a fitted spatial logistic regresson model

Usage

# S3 method for slrm
simulate(object, nsim = 1, seed=NULL, ...,
         window=NULL, covariates=NULL, verbose=TRUE, drop=FALSE)

Arguments

object

Fitted spatial logistic regression model. An object of class "slrm".

nsim

Number of simulated realisations.

seed

an object specifying whether and how to initialise the random number generator. Either NULL or an integer that will be used in a call to set.seed before simulating the point patterns.

…

Ignored.

window

Optional. Window (object of class "owin") in which the model should be simulated.

covariates

Optional. A named list containing new values for the covariates in the model.

verbose

Logical. Whether to print progress reports (when nsim > 1).

drop

Logical. If nsim=1 and drop=TRUE, the result will be a point pattern, rather than a list containing a point pattern.

Value

A list of length nsim containing simulated point patterns (objects of class "ppp").

The return value also carries an attribute "seed" that captures the initial state of the random number generator. See Details.

Details

This function is a method for the generic function simulate for the class "slrm" of fitted spatial logistic regression models.

Simulations are performed by rpoispp after the intensity has been computed by predict.slrm.

The return value is a list of point patterns. It also carries an attribute "seed" that captures the initial state of the random number generator. This follows the convention used in simulate.lm (see simulate). It can be used to force a sequence of simulations to be repeated exactly, as shown in the examples for simulate.

See Also

slrm, rpoispp, simulate.ppm, simulate.kppm, simulate

Examples

# NOT RUN {
  X <- copper$SouthPoints
  fit <- slrm(X ~ 1)
  simulate(fit, 2)
  fitxy <- slrm(X ~ x+y)
  simulate(fitxy, 2, window=square(2))
# }